{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import json\n",
    "import os\n",
    "from collections import defaultdict\n",
    "\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "from IPython.display import display\n",
    "\n",
    "\n",
    "plt.rcParams[\"font.family\"] = \"Times New Roman\"\n",
    "plt.rcParams[\"mathtext.fontset\"] = \"cm\"\n",
    "\n",
    "matplotlib.rcParams[\"pdf.fonttype\"] = 42\n",
    "matplotlib.rcParams[\"ps.fonttype\"] = 42"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  background-color: #f99355;\n",
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       "  background-color: #18954f;\n",
       "  color: #f1f1f1;\n",
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       "  background-color: #006837;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_c8f81_row3_col6 {\n",
       "  background-color: #f1f9ac;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_c8f81_row3_col7 {\n",
       "  background-color: #fff7b2;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_c8f81_row3_col10, #T_c8f81_row5_col6 {\n",
       "  background-color: #fdb96a;\n",
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       "#T_c8f81_row3_col11 {\n",
       "  background-color: #fffdbc;\n",
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       "#T_c8f81_row4_col0 {\n",
       "  background-color: #ab0626;\n",
       "  color: #f1f1f1;\n",
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       "#T_c8f81_row4_col3 {\n",
       "  background-color: #fa9857;\n",
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       "#T_c8f81_row4_col4 {\n",
       "  background-color: #7ac665;\n",
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       "  background-color: #f46d43;\n",
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       "  background-color: #66bd63;\n",
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       "  background-color: #b7e075;\n",
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       "  background-color: #e44c34;\n",
       "  color: #f1f1f1;\n",
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       "  background-color: #eff8aa;\n",
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       "  background-color: #249d53;\n",
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       "  background-color: #dff293;\n",
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       "  background-color: #05713c;\n",
       "  color: #f1f1f1;\n",
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       "#T_c8f81_row6_col5, #T_c8f81_row10_col5, #T_c8f81_row11_col5 {\n",
       "  background-color: #4bb05c;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_c8f81_row6_col7 {\n",
       "  background-color: #60ba62;\n",
       "  color: #f1f1f1;\n",
       "}\n",
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       "  background-color: #78c565;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_c8f81_row6_col11 {\n",
       "  background-color: #17934e;\n",
       "  color: #f1f1f1;\n",
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       "#T_c8f81_row7_col0 {\n",
       "  background-color: #15904c;\n",
       "  color: #f1f1f1;\n",
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       "  background-color: #d5ed88;\n",
       "  color: #000000;\n",
       "}\n",
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       "  background-color: #279f53;\n",
       "  color: #f1f1f1;\n",
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       "#T_c8f81_row7_col10, #T_c8f81_row13_col10 {\n",
       "  background-color: #1e9a51;\n",
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       "#T_c8f81_row8_col0 {\n",
       "  background-color: #b91326;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_c8f81_row8_col6 {\n",
       "  background-color: #b71126;\n",
       "  color: #f1f1f1;\n",
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       "#T_c8f81_row8_col10 {\n",
       "  background-color: #dd3d2d;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_c8f81_row8_col11 {\n",
       "  background-color: #fdbb6c;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_c8f81_row9_col0 {\n",
       "  background-color: #eb5a3a;\n",
       "  color: #f1f1f1;\n",
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       "#T_c8f81_row9_col4 {\n",
       "  background-color: #fdaf62;\n",
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       "  background-color: #e2f397;\n",
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       "  background-color: #feeb9d;\n",
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       "  background-color: #42ac5a;\n",
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       "}\n",
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       "  color: #f1f1f1;\n",
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       "  background-color: #0e8245;\n",
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       "  background-color: #fffbb8;\n",
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       "  background-color: #6ec064;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_c8f81_row12_col0 {\n",
       "  background-color: #d42d27;\n",
       "  color: #f1f1f1;\n",
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       "#T_c8f81_row12_col6 {\n",
       "  background-color: #f57547;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_c8f81_row12_col7 {\n",
       "  background-color: #fedc88;\n",
       "  color: #000000;\n",
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       "#T_c8f81_row12_col10 {\n",
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       "#T_c8f81_row13_col0 {\n",
       "  background-color: #f67c4a;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_c8f81_row13_col3 {\n",
       "  background-color: #91d068;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_c8f81_row13_col4, #T_c8f81_row14_col4 {\n",
       "  background-color: #c62027;\n",
       "  color: #f1f1f1;\n",
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       "#T_c8f81_row13_col6 {\n",
       "  background-color: #e3f399;\n",
       "  color: #000000;\n",
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       "#T_c8f81_row13_col7 {\n",
       "  background-color: #c9e881;\n",
       "  color: #000000;\n",
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       "#T_c8f81_row14_col0 {\n",
       "  background-color: #fffab6;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_c8f81_row14_col6 {\n",
       "  background-color: #9dd569;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_c8f81_row14_col10 {\n",
       "  background-color: #138c4a;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_c8f81_row14_col11 {\n",
       "  background-color: #fee695;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_c8f81_row15_col4 {\n",
       "  background-color: #e24731;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_c8f81_row15_col7 {\n",
       "  background-color: #07753e;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_c8f81_row15_col11 {\n",
       "  background-color: #f4fab0;\n",
       "  color: #000000;\n",
       "}\n",
       "</style>\n",
       "<table id=\"T_c8f81\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th id=\"T_c8f81_level0_col0\" class=\"col_heading level0 col0\" >num_params</th>\n",
       "      <th id=\"T_c8f81_level0_col1\" class=\"col_heading level0 col1\" >gate_k</th>\n",
       "      <th id=\"T_c8f81_level0_col2\" class=\"col_heading level0 col2\" >k</th>\n",
       "      <th id=\"T_c8f81_level0_col3\" class=\"col_heading level0 col3\" >cola</th>\n",
       "      <th id=\"T_c8f81_level0_col4\" class=\"col_heading level0 col4\" >mnli</th>\n",
       "      <th id=\"T_c8f81_level0_col5\" class=\"col_heading level0 col5\" >mrpc</th>\n",
       "      <th id=\"T_c8f81_level0_col6\" class=\"col_heading level0 col6\" >qnli</th>\n",
       "      <th id=\"T_c8f81_level0_col7\" class=\"col_heading level0 col7\" >qqp</th>\n",
       "      <th id=\"T_c8f81_level0_col8\" class=\"col_heading level0 col8\" >rte</th>\n",
       "      <th id=\"T_c8f81_level0_col9\" class=\"col_heading level0 col9\" >sst2</th>\n",
       "      <th id=\"T_c8f81_level0_col10\" class=\"col_heading level0 col10\" >stsb</th>\n",
       "      <th id=\"T_c8f81_level0_col11\" class=\"col_heading level0 col11\" >average</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_c8f81_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
       "      <td id=\"T_c8f81_row0_col0\" class=\"data row0 col0\" >312368384</td>\n",
       "      <td id=\"T_c8f81_row0_col1\" class=\"data row0 col1\" >4</td>\n",
       "      <td id=\"T_c8f81_row0_col2\" class=\"data row0 col2\" >16</td>\n",
       "      <td id=\"T_c8f81_row0_col3\" class=\"data row0 col3\" >0.720038</td>\n",
       "      <td id=\"T_c8f81_row0_col4\" class=\"data row0 col4\" >0.841671</td>\n",
       "      <td id=\"T_c8f81_row0_col5\" class=\"data row0 col5\" >0.843137</td>\n",
       "      <td id=\"T_c8f81_row0_col6\" class=\"data row0 col6\" >0.912868</td>\n",
       "      <td id=\"T_c8f81_row0_col7\" class=\"data row0 col7\" >0.846846</td>\n",
       "      <td id=\"T_c8f81_row0_col8\" class=\"data row0 col8\" >0.841155</td>\n",
       "      <td id=\"T_c8f81_row0_col9\" class=\"data row0 col9\" >0.933486</td>\n",
       "      <td id=\"T_c8f81_row0_col10\" class=\"data row0 col10\" >0.870168</td>\n",
       "      <td id=\"T_c8f81_row0_col11\" class=\"data row0 col11\" >85.117129</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_c8f81_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
       "      <td id=\"T_c8f81_row1_col0\" class=\"data row1 col0\" >370842880</td>\n",
       "      <td id=\"T_c8f81_row1_col1\" class=\"data row1 col1\" >4</td>\n",
       "      <td id=\"T_c8f81_row1_col2\" class=\"data row1 col2\" >32</td>\n",
       "      <td id=\"T_c8f81_row1_col3\" class=\"data row1 col3\" >0.724832</td>\n",
       "      <td id=\"T_c8f81_row1_col4\" class=\"data row1 col4\" >0.842180</td>\n",
       "      <td id=\"T_c8f81_row1_col5\" class=\"data row1 col5\" >0.840686</td>\n",
       "      <td id=\"T_c8f81_row1_col6\" class=\"data row1 col6\" >0.913784</td>\n",
       "      <td id=\"T_c8f81_row1_col7\" class=\"data row1 col7\" >0.847588</td>\n",
       "      <td id=\"T_c8f81_row1_col8\" class=\"data row1 col8\" >0.837545</td>\n",
       "      <td id=\"T_c8f81_row1_col9\" class=\"data row1 col9\" >0.932339</td>\n",
       "      <td id=\"T_c8f81_row1_col10\" class=\"data row1 col10\" >0.870828</td>\n",
       "      <td id=\"T_c8f81_row1_col11\" class=\"data row1 col11\" >85.122299</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_c8f81_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
       "      <td id=\"T_c8f81_row2_col0\" class=\"data row2 col0\" >487791872</td>\n",
       "      <td id=\"T_c8f81_row2_col1\" class=\"data row2 col1\" >4</td>\n",
       "      <td id=\"T_c8f81_row2_col2\" class=\"data row2 col2\" >64</td>\n",
       "      <td id=\"T_c8f81_row2_col3\" class=\"data row2 col3\" >0.727709</td>\n",
       "      <td id=\"T_c8f81_row2_col4\" class=\"data row2 col4\" >0.842486</td>\n",
       "      <td id=\"T_c8f81_row2_col5\" class=\"data row2 col5\" >0.838235</td>\n",
       "      <td id=\"T_c8f81_row2_col6\" class=\"data row2 col6\" >0.913784</td>\n",
       "      <td id=\"T_c8f81_row2_col7\" class=\"data row2 col7\" >0.848133</td>\n",
       "      <td id=\"T_c8f81_row2_col8\" class=\"data row2 col8\" >0.837545</td>\n",
       "      <td id=\"T_c8f81_row2_col9\" class=\"data row2 col9\" >0.933486</td>\n",
       "      <td id=\"T_c8f81_row2_col10\" class=\"data row2 col10\" >0.871877</td>\n",
       "      <td id=\"T_c8f81_row2_col11\" class=\"data row2 col11\" >85.165678</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_c8f81_level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
       "      <td id=\"T_c8f81_row3_col0\" class=\"data row3 col0\" >721689856</td>\n",
       "      <td id=\"T_c8f81_row3_col1\" class=\"data row3 col1\" >4</td>\n",
       "      <td id=\"T_c8f81_row3_col2\" class=\"data row3 col2\" >128</td>\n",
       "      <td id=\"T_c8f81_row3_col3\" class=\"data row3 col3\" >0.728667</td>\n",
       "      <td id=\"T_c8f81_row3_col4\" class=\"data row3 col4\" >0.842486</td>\n",
       "      <td id=\"T_c8f81_row3_col5\" class=\"data row3 col5\" >0.843137</td>\n",
       "      <td id=\"T_c8f81_row3_col6\" class=\"data row3 col6\" >0.914150</td>\n",
       "      <td id=\"T_c8f81_row3_col7\" class=\"data row3 col7\" >0.848429</td>\n",
       "      <td id=\"T_c8f81_row3_col8\" class=\"data row3 col8\" >0.841155</td>\n",
       "      <td id=\"T_c8f81_row3_col9\" class=\"data row3 col9\" >0.933486</td>\n",
       "      <td id=\"T_c8f81_row3_col10\" class=\"data row3 col10\" >0.871944</td>\n",
       "      <td id=\"T_c8f81_row3_col11\" class=\"data row3 col11\" >85.293188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_c8f81_level0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
       "      <td id=\"T_c8f81_row4_col0\" class=\"data row4 col0\" >318684416</td>\n",
       "      <td id=\"T_c8f81_row4_col1\" class=\"data row4 col1\" >8</td>\n",
       "      <td id=\"T_c8f81_row4_col2\" class=\"data row4 col2\" >16</td>\n",
       "      <td id=\"T_c8f81_row4_col3\" class=\"data row4 col3\" >0.723873</td>\n",
       "      <td id=\"T_c8f81_row4_col4\" class=\"data row4 col4\" >0.841773</td>\n",
       "      <td id=\"T_c8f81_row4_col5\" class=\"data row4 col5\" >0.850490</td>\n",
       "      <td id=\"T_c8f81_row4_col6\" class=\"data row4 col6\" >0.911404</td>\n",
       "      <td id=\"T_c8f81_row4_col7\" class=\"data row4 col7\" >0.847514</td>\n",
       "      <td id=\"T_c8f81_row4_col8\" class=\"data row4 col8\" >0.844765</td>\n",
       "      <td id=\"T_c8f81_row4_col9\" class=\"data row4 col9\" >0.934633</td>\n",
       "      <td id=\"T_c8f81_row4_col10\" class=\"data row4 col10\" >0.870978</td>\n",
       "      <td id=\"T_c8f81_row4_col11\" class=\"data row4 col11\" >85.317882</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_c8f81_level0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
       "      <td id=\"T_c8f81_row5_col0\" class=\"data row5 col0\" >377158912</td>\n",
       "      <td id=\"T_c8f81_row5_col1\" class=\"data row5 col1\" >8</td>\n",
       "      <td id=\"T_c8f81_row5_col2\" class=\"data row5 col2\" >32</td>\n",
       "      <td id=\"T_c8f81_row5_col3\" class=\"data row5 col3\" >0.731544</td>\n",
       "      <td id=\"T_c8f81_row5_col4\" class=\"data row5 col4\" >0.842282</td>\n",
       "      <td id=\"T_c8f81_row5_col5\" class=\"data row5 col5\" >0.850490</td>\n",
       "      <td id=\"T_c8f81_row5_col6\" class=\"data row5 col6\" >0.913051</td>\n",
       "      <td id=\"T_c8f81_row5_col7\" class=\"data row5 col7\" >0.848800</td>\n",
       "      <td id=\"T_c8f81_row5_col8\" class=\"data row5 col8\" >0.848375</td>\n",
       "      <td id=\"T_c8f81_row5_col9\" class=\"data row5 col9\" >0.934633</td>\n",
       "      <td id=\"T_c8f81_row5_col10\" class=\"data row5 col10\" >0.873389</td>\n",
       "      <td id=\"T_c8f81_row5_col11\" class=\"data row5 col11\" >85.532067</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_c8f81_level0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
       "      <td id=\"T_c8f81_row6_col0\" class=\"data row6 col0\" >494107904</td>\n",
       "      <td id=\"T_c8f81_row6_col1\" class=\"data row6 col1\" >8</td>\n",
       "      <td id=\"T_c8f81_row6_col2\" class=\"data row6 col2\" >64</td>\n",
       "      <td id=\"T_c8f81_row6_col3\" class=\"data row6 col3\" >0.733461</td>\n",
       "      <td id=\"T_c8f81_row6_col4\" class=\"data row6 col4\" >0.842690</td>\n",
       "      <td id=\"T_c8f81_row6_col5\" class=\"data row6 col5\" >0.848039</td>\n",
       "      <td id=\"T_c8f81_row6_col6\" class=\"data row6 col6\" >0.913784</td>\n",
       "      <td id=\"T_c8f81_row6_col7\" class=\"data row6 col7\" >0.849542</td>\n",
       "      <td id=\"T_c8f81_row6_col8\" class=\"data row6 col8\" >0.844765</td>\n",
       "      <td id=\"T_c8f81_row6_col9\" class=\"data row6 col9\" >0.934633</td>\n",
       "      <td id=\"T_c8f81_row6_col10\" class=\"data row6 col10\" >0.874408</td>\n",
       "      <td id=\"T_c8f81_row6_col11\" class=\"data row6 col11\" >85.516534</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_c8f81_level0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
       "      <td id=\"T_c8f81_row7_col0\" class=\"data row7 col0\" >728005888</td>\n",
       "      <td id=\"T_c8f81_row7_col1\" class=\"data row7 col1\" >8</td>\n",
       "      <td id=\"T_c8f81_row7_col2\" class=\"data row7 col2\" >128</td>\n",
       "      <td id=\"T_c8f81_row7_col3\" class=\"data row7 col3\" >0.733461</td>\n",
       "      <td id=\"T_c8f81_row7_col4\" class=\"data row7 col4\" >0.842792</td>\n",
       "      <td id=\"T_c8f81_row7_col5\" class=\"data row7 col5\" >0.845588</td>\n",
       "      <td id=\"T_c8f81_row7_col6\" class=\"data row7 col6\" >0.914516</td>\n",
       "      <td id=\"T_c8f81_row7_col7\" class=\"data row7 col7\" >0.849790</td>\n",
       "      <td id=\"T_c8f81_row7_col8\" class=\"data row7 col8\" >0.848375</td>\n",
       "      <td id=\"T_c8f81_row7_col9\" class=\"data row7 col9\" >0.935780</td>\n",
       "      <td id=\"T_c8f81_row7_col10\" class=\"data row7 col10\" >0.875088</td>\n",
       "      <td id=\"T_c8f81_row7_col11\" class=\"data row7 col11\" >85.567374</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_c8f81_level0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
       "      <td id=\"T_c8f81_row8_col0\" class=\"data row8 col0\" >331316480</td>\n",
       "      <td id=\"T_c8f81_row8_col1\" class=\"data row8 col1\" >16</td>\n",
       "      <td id=\"T_c8f81_row8_col2\" class=\"data row8 col2\" >16</td>\n",
       "      <td id=\"T_c8f81_row8_col3\" class=\"data row8 col3\" >0.724832</td>\n",
       "      <td id=\"T_c8f81_row8_col4\" class=\"data row8 col4\" >0.838411</td>\n",
       "      <td id=\"T_c8f81_row8_col5\" class=\"data row8 col5\" >0.843137</td>\n",
       "      <td id=\"T_c8f81_row8_col6\" class=\"data row8 col6\" >0.911587</td>\n",
       "      <td id=\"T_c8f81_row8_col7\" class=\"data row8 col7\" >0.847885</td>\n",
       "      <td id=\"T_c8f81_row8_col8\" class=\"data row8 col8\" >0.844765</td>\n",
       "      <td id=\"T_c8f81_row8_col9\" class=\"data row8 col9\" >0.934633</td>\n",
       "      <td id=\"T_c8f81_row8_col10\" class=\"data row8 col10\" >0.870852</td>\n",
       "      <td id=\"T_c8f81_row8_col11\" class=\"data row8 col11\" >85.201282</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_c8f81_level0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
       "      <td id=\"T_c8f81_row9_col0\" class=\"data row9 col0\" >389790976</td>\n",
       "      <td id=\"T_c8f81_row9_col1\" class=\"data row9 col1\" >16</td>\n",
       "      <td id=\"T_c8f81_row9_col2\" class=\"data row9 col2\" >32</td>\n",
       "      <td id=\"T_c8f81_row9_col3\" class=\"data row9 col3\" >0.731544</td>\n",
       "      <td id=\"T_c8f81_row9_col4\" class=\"data row9 col4\" >0.839735</td>\n",
       "      <td id=\"T_c8f81_row9_col5\" class=\"data row9 col5\" >0.845588</td>\n",
       "      <td id=\"T_c8f81_row9_col6\" class=\"data row9 col6\" >0.913967</td>\n",
       "      <td id=\"T_c8f81_row9_col7\" class=\"data row9 col7\" >0.848776</td>\n",
       "      <td id=\"T_c8f81_row9_col8\" class=\"data row9 col8\" >0.841155</td>\n",
       "      <td id=\"T_c8f81_row9_col9\" class=\"data row9 col9\" >0.934633</td>\n",
       "      <td id=\"T_c8f81_row9_col10\" class=\"data row9 col10\" >0.872569</td>\n",
       "      <td id=\"T_c8f81_row9_col11\" class=\"data row9 col11\" >85.349581</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_c8f81_level0_row10\" class=\"row_heading level0 row10\" >10</th>\n",
       "      <td id=\"T_c8f81_row10_col0\" class=\"data row10 col0\" >506739968</td>\n",
       "      <td id=\"T_c8f81_row10_col1\" class=\"data row10 col1\" >16</td>\n",
       "      <td id=\"T_c8f81_row10_col2\" class=\"data row10 col2\" >64</td>\n",
       "      <td id=\"T_c8f81_row10_col3\" class=\"data row10 col3\" >0.732502</td>\n",
       "      <td id=\"T_c8f81_row10_col4\" class=\"data row10 col4\" >0.840346</td>\n",
       "      <td id=\"T_c8f81_row10_col5\" class=\"data row10 col5\" >0.848039</td>\n",
       "      <td id=\"T_c8f81_row10_col6\" class=\"data row10 col6\" >0.914516</td>\n",
       "      <td id=\"T_c8f81_row10_col7\" class=\"data row10 col7\" >0.849666</td>\n",
       "      <td id=\"T_c8f81_row10_col8\" class=\"data row10 col8\" >0.844765</td>\n",
       "      <td id=\"T_c8f81_row10_col9\" class=\"data row10 col9\" >0.934633</td>\n",
       "      <td id=\"T_c8f81_row10_col10\" class=\"data row10 col10\" >0.872973</td>\n",
       "      <td id=\"T_c8f81_row10_col11\" class=\"data row10 col11\" >85.468013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_c8f81_level0_row11\" class=\"row_heading level0 row11\" >11</th>\n",
       "      <td id=\"T_c8f81_row11_col0\" class=\"data row11 col0\" >740637952</td>\n",
       "      <td id=\"T_c8f81_row11_col1\" class=\"data row11 col1\" >16</td>\n",
       "      <td id=\"T_c8f81_row11_col2\" class=\"data row11 col2\" >128</td>\n",
       "      <td id=\"T_c8f81_row11_col3\" class=\"data row11 col3\" >0.732502</td>\n",
       "      <td id=\"T_c8f81_row11_col4\" class=\"data row11 col4\" >0.840346</td>\n",
       "      <td id=\"T_c8f81_row11_col5\" class=\"data row11 col5\" >0.848039</td>\n",
       "      <td id=\"T_c8f81_row11_col6\" class=\"data row11 col6\" >0.915248</td>\n",
       "      <td id=\"T_c8f81_row11_col7\" class=\"data row11 col7\" >0.850186</td>\n",
       "      <td id=\"T_c8f81_row11_col8\" class=\"data row11 col8\" >0.841155</td>\n",
       "      <td id=\"T_c8f81_row11_col9\" class=\"data row11 col9\" >0.935780</td>\n",
       "      <td id=\"T_c8f81_row11_col10\" class=\"data row11 col10\" >0.872839</td>\n",
       "      <td id=\"T_c8f81_row11_col11\" class=\"data row11 col11\" >85.451197</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_c8f81_level0_row12\" class=\"row_heading level0 row12\" >12</th>\n",
       "      <td id=\"T_c8f81_row12_col0\" class=\"data row12 col0\" >356580608</td>\n",
       "      <td id=\"T_c8f81_row12_col1\" class=\"data row12 col1\" >32</td>\n",
       "      <td id=\"T_c8f81_row12_col2\" class=\"data row12 col2\" >16</td>\n",
       "      <td id=\"T_c8f81_row12_col3\" class=\"data row12 col3\" >0.725791</td>\n",
       "      <td id=\"T_c8f81_row12_col4\" class=\"data row12 col4\" >0.838411</td>\n",
       "      <td id=\"T_c8f81_row12_col5\" class=\"data row12 col5\" >0.838235</td>\n",
       "      <td id=\"T_c8f81_row12_col6\" class=\"data row12 col6\" >0.912502</td>\n",
       "      <td id=\"T_c8f81_row12_col7\" class=\"data row12 col7\" >0.848157</td>\n",
       "      <td id=\"T_c8f81_row12_col8\" class=\"data row12 col8\" >0.830325</td>\n",
       "      <td id=\"T_c8f81_row12_col9\" class=\"data row12 col9\" >0.935780</td>\n",
       "      <td id=\"T_c8f81_row12_col10\" class=\"data row12 col10\" >0.872677</td>\n",
       "      <td id=\"T_c8f81_row12_col11\" class=\"data row12 col11\" >85.023477</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_c8f81_level0_row13\" class=\"row_heading level0 row13\" >13</th>\n",
       "      <td id=\"T_c8f81_row13_col0\" class=\"data row13 col0\" >415055104</td>\n",
       "      <td id=\"T_c8f81_row13_col1\" class=\"data row13 col1\" >32</td>\n",
       "      <td id=\"T_c8f81_row13_col2\" class=\"data row13 col2\" >32</td>\n",
       "      <td id=\"T_c8f81_row13_col3\" class=\"data row13 col3\" >0.730585</td>\n",
       "      <td id=\"T_c8f81_row13_col4\" class=\"data row13 col4\" >0.838716</td>\n",
       "      <td id=\"T_c8f81_row13_col5\" class=\"data row13 col5\" >0.843137</td>\n",
       "      <td id=\"T_c8f81_row13_col6\" class=\"data row13 col6\" >0.914333</td>\n",
       "      <td id=\"T_c8f81_row13_col7\" class=\"data row13 col7\" >0.848949</td>\n",
       "      <td id=\"T_c8f81_row13_col8\" class=\"data row13 col8\" >0.833935</td>\n",
       "      <td id=\"T_c8f81_row13_col9\" class=\"data row13 col9\" >0.935780</td>\n",
       "      <td id=\"T_c8f81_row13_col10\" class=\"data row13 col10\" >0.875086</td>\n",
       "      <td id=\"T_c8f81_row13_col11\" class=\"data row13 col11\" >85.256515</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_c8f81_level0_row14\" class=\"row_heading level0 row14\" >14</th>\n",
       "      <td id=\"T_c8f81_row14_col0\" class=\"data row14 col0\" >532004096</td>\n",
       "      <td id=\"T_c8f81_row14_col1\" class=\"data row14 col1\" >32</td>\n",
       "      <td id=\"T_c8f81_row14_col2\" class=\"data row14 col2\" >64</td>\n",
       "      <td id=\"T_c8f81_row14_col3\" class=\"data row14 col3\" >0.733461</td>\n",
       "      <td id=\"T_c8f81_row14_col4\" class=\"data row14 col4\" >0.838716</td>\n",
       "      <td id=\"T_c8f81_row14_col5\" class=\"data row14 col5\" >0.838235</td>\n",
       "      <td id=\"T_c8f81_row14_col6\" class=\"data row14 col6\" >0.915065</td>\n",
       "      <td id=\"T_c8f81_row14_col7\" class=\"data row14 col7\" >0.849740</td>\n",
       "      <td id=\"T_c8f81_row14_col8\" class=\"data row14 col8\" >0.833935</td>\n",
       "      <td id=\"T_c8f81_row14_col9\" class=\"data row14 col9\" >0.935780</td>\n",
       "      <td id=\"T_c8f81_row14_col10\" class=\"data row14 col10\" >0.875260</td>\n",
       "      <td id=\"T_c8f81_row14_col11\" class=\"data row14 col11\" >85.252415</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_c8f81_level0_row15\" class=\"row_heading level0 row15\" >15</th>\n",
       "      <td id=\"T_c8f81_row15_col0\" class=\"data row15 col0\" >765902080</td>\n",
       "      <td id=\"T_c8f81_row15_col1\" class=\"data row15 col1\" >32</td>\n",
       "      <td id=\"T_c8f81_row15_col2\" class=\"data row15 col2\" >128</td>\n",
       "      <td id=\"T_c8f81_row15_col3\" class=\"data row15 col3\" >0.734420</td>\n",
       "      <td id=\"T_c8f81_row15_col4\" class=\"data row15 col4\" >0.839022</td>\n",
       "      <td id=\"T_c8f81_row15_col5\" class=\"data row15 col5\" >0.835784</td>\n",
       "      <td id=\"T_c8f81_row15_col6\" class=\"data row15 col6\" >0.916529</td>\n",
       "      <td id=\"T_c8f81_row15_col7\" class=\"data row15 col7\" >0.850087</td>\n",
       "      <td id=\"T_c8f81_row15_col8\" class=\"data row15 col8\" >0.837545</td>\n",
       "      <td id=\"T_c8f81_row15_col9\" class=\"data row15 col9\" >0.935780</td>\n",
       "      <td id=\"T_c8f81_row15_col10\" class=\"data row15 col10\" >0.875677</td>\n",
       "      <td id=\"T_c8f81_row15_col11\" class=\"data row15 col11\" >85.310548</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7f1c95232c20>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_dir = \"/workspace/svd_subspace/outputs/flan-t5-base/glue_text_generation/\"\n",
    "moe_data = defaultdict(list)\n",
    "for gate_k in [4, 8, 16, 32]:\n",
    "    for k in [16, 32, 64, 128]:\n",
    "        file_name = f\"gate_k={gate_k}_k={k}.json\"\n",
    "        file_name = os.path.join(data_dir, file_name)\n",
    "        if not os.path.exists(file_name):\n",
    "            # print(f\"File {file_name} does not exist\")\n",
    "            continue\n",
    "        with open(file_name) as f:\n",
    "            data = json.load(f)\n",
    "        moe_data[\"num_params\"].append(data[\"model_info\"][\"all_params\"])\n",
    "        moe_data[\"gate_k\"].append(gate_k)\n",
    "        moe_data[\"k\"].append(k)\n",
    "        scores = {}\n",
    "        for key in data:\n",
    "            if key == \"model_info\":\n",
    "                continue\n",
    "            scores[key] = (\n",
    "                data[key][\"accuracy\"]\n",
    "                if \"accuracy\" in data[key]\n",
    "                else data[key][\"spearman_rho\"]\n",
    "            )\n",
    "        average_accuracy = np.mean(list(scores.values())) * 100\n",
    "        for key in scores:\n",
    "            moe_data[key].append(scores[key])\n",
    "        moe_data[\"average\"].append(average_accuracy)\n",
    "moe_data = pd.DataFrame(moe_data)\n",
    "\n",
    "# 使用 Styler 对象并应用背景颜色渐变\n",
    "styled_df = moe_data.style.background_gradient(cmap=\"RdYlGn\")\n",
    "\n",
    "# 显示结果\n",
    "styled_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_762769/96687780.py:5: FutureWarning: Setting an item of incompatible dtype is deprecated and will raise an error in a future version of pandas. Value 'Dense' has dtype incompatible with int64, please explicitly cast to a compatible dtype first.\n",
      "  plot_data.loc[plot_data[\"k\"] == -1, \"k\"] = \"Dense\"\n",
      "'created' timestamp seems very low; regarding as unix timestamp\n",
      "'modified' timestamp seems very low; regarding as unix timestamp\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_762769/96687780.py:20: FutureWarning: Setting an item of incompatible dtype is deprecated and will raise an error in a future version of pandas. Value 'Dense' has dtype incompatible with int64, please explicitly cast to a compatible dtype first.\n",
      "  plot_data.loc[plot_data[\"k\"] == -1, \"k\"] = \"Dense\"\n",
      "'created' timestamp seems very low; regarding as unix timestamp\n",
      "'modified' timestamp seems very low; regarding as unix timestamp\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "matplotlib.rcParams[\"font.size\"] = 28\n",
    "\n",
    "plot_data = moe_data.copy()\n",
    "plot_data[\"method\"] = \"Ours\"\n",
    "plot_data.loc[plot_data[\"k\"] == -1, \"k\"] = \"Dense\"\n",
    "pivot_data = (\n",
    "    plot_data[[\"gate_k\", \"k\", \"average\"]]\n",
    "    .pivot(index=\"gate_k\", columns=\"k\", values=\"average\")\n",
    "    .copy()\n",
    ")\n",
    "\n",
    "sns.heatmap(data=pivot_data, annot=True, fmt=\".1f\", cmap=\"RdYlGn\")\n",
    "plt.xlabel(\"$k$\")\n",
    "plt.ylabel(\"$k_{gate}$\")\n",
    "plt.savefig(\"flan-t5-base_hp-acc.pdf\", bbox_inches=\"tight\")\n",
    "plt.show()\n",
    "\n",
    "plot_data = moe_data.copy()\n",
    "plot_data[\"method\"] = \"Ours\"\n",
    "plot_data.loc[plot_data[\"k\"] == -1, \"k\"] = \"Dense\"\n",
    "plot_data[\"num_params\"] = plot_data[\"num_params\"] / 247577856\n",
    "pivot_data = (\n",
    "    plot_data[[\"gate_k\", \"k\", \"num_params\"]]\n",
    "    .pivot(index=\"gate_k\", columns=\"k\", values=\"num_params\")\n",
    "    .copy()\n",
    ")\n",
    "\n",
    "sns.heatmap(data=pivot_data, annot=True, fmt=\".2f\", cmap=\"RdYlGn_r\")\n",
    "plt.xlabel(\"$k$\")\n",
    "plt.ylabel(\"$k_{gate}$\")\n",
    "plt.savefig(\"flan-t5-base_hp-params.pdf\", bbox_inches=\"tight\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "base",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.14"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
